Merge pull request #17 from EMSL-Computing/bugfix/mass_filter

hard code mass filter columns
EMSL-Computing · Feb 9, 2023 · dd3bc3a · dd3bc3a
2 parents 6df6a14 + b10ac32
commit dd3bc3a
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Showing 3 changed files with 11 additions and 7 deletions.
diff --git a/R/applyFilt.R b/R/applyFilt.R
@@ -124,17 +124,16 @@ applyFilt.massFilt <- function(filter_object, ftmsObj, min_mass = 200, max_mass
     if(length(max_mass) != 1) stop("max_mass must be of length 1")
 
     edata_cname <- getEDataColName(ftmsObj)
-    mass_cname = getMassColName(ftmsObj)
 
-    mass_info <- filter_object[,mass_cname]
+    mass_info <- filter_object[,"Mass"]
 
     # get indices for which ones meet the requirement #
     inds <- which(mass_info <= max_mass & mass_info >= min_mass)
 
     if(length(inds) < 1) stop("Filtering using the specified minimum and maximum masses results in no peaks left in the data.")
 
     # sample identifiers to keep #
-    edata_ids = filter_object[inds, edata_cname]
+    edata_ids = filter_object[inds, "ID__"]
 
     temp_edata = ftmsObj$e_data[which(ftmsObj$e_data[,edata_cname] %in% edata_ids),]
     temp_emeta = ftmsObj$e_meta[which(ftmsObj$e_meta[,edata_cname] %in% edata_ids),]

diff --git a/R/mass_filter.R b/R/mass_filter.R
@@ -26,11 +26,10 @@ mass_filter <- function(ftmsObj){
   mass_id = getMassColName(ftmsObj)
 
   # pull two columns from e_meta #
-  res = data.frame(ID = ftmsObj$e_meta[,edata_id], ftmsObj$e_meta[,mass_id])
-  names(res)[2] = mass_id
+  res = data.frame(`ID__` = ftmsObj$e_meta[,edata_id], Mass = ftmsObj$e_meta[,mass_id])
 
   # make sure mass column is numeric #
-  res[,mass_id] = as.numeric(as.character(res[,mass_id]))
+  res[,"Mass"] = as.numeric(as.character(res[,"Mass"]))
 
   class(res) = c("massFilt", "data.frame")
 

diff --git a/tests/testthat/test_filters.R b/tests/testthat/test_filters.R
@@ -6,11 +6,17 @@ context("filtering on peakData objects")
 test_that("mass filters work correctly on peakData", {
   data("examplePeakData")
 
+  # test with a random mass column name and make sure it is unique
+  tmp_masscol = sample(LETTERS, 10)
+  tmp_masscol = make.unique(c(colnames(examplePeakData$e_meta), tmp_masscol))[ncol(examplePeakData$e_meta) + 1]
+
+  examplePeakData$e_meta[[tmp_masscol]] <- examplePeakData$e_meta[[getMassColName(examplePeakData)]]
+  attributes(examplePeakData)$cnames$mass_cname = tmp_masscol
+
   filtData <- mass_filter(examplePeakData)
   expect_true(inherits(filtData, "massFilt"))
   expect_true(inherits(filtData, "data.frame"))
   expect_true(ncol(filtData) == 2)
-  expect_true(all(c(getEDataColName(examplePeakData), getMassColName(examplePeakData)) %in% colnames(filtData)))
 
   peakObj2 <- applyFilt(filtData, examplePeakData, min_mass = 200, max_mass = 900)
   expect_true(inherits(peakObj2, "peakData"))